Overview

Dataset statistics

Number of variables18
Number of observations2411
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory357.9 KiB
Average record size in memory152.0 B

Variable types

DateTime1
TimeSeries15
Numeric2

Timeseries statistics

Number of series15
Time series length2411
Starting point2010-01-26 00:00:00
Ending point2019-08-26 00:00:00
Period1 day, 10 hours and 50 minutes
2026-02-01T18:38:31.674008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:31.976237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

AD is highly overall correlated with OBVHigh correlation
ATR is highly overall correlated with TRANGEHigh correlation
CMO is highly overall correlated with MFI and 2 other fieldsHigh correlation
EMA is highly overall correlated with KAMA and 6 other fieldsHigh correlation
KAMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MFI is highly overall correlated with CMO and 2 other fieldsHigh correlation
MidPrice is highly overall correlated with EMA and 6 other fieldsHigh correlation
NATR is highly overall correlated with EMA and 7 other fieldsHigh correlation
OBV is highly overall correlated with AD and 1 other fieldsHigh correlation
ROC is highly overall correlated with CMO and 2 other fieldsHigh correlation
TRANGE is highly overall correlated with ATRHigh correlation
TSF is highly overall correlated with EMA and 6 other fieldsHigh correlation
WILLR is highly overall correlated with CMO and 2 other fieldsHigh correlation
WMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is non stationaryNon stationary
MA is non stationaryNon stationary
EMA is non stationaryNon stationary
KAMA is non stationaryNon stationary
WMA is non stationaryNon stationary
MidPrice is non stationaryNon stationary
AD is non stationaryNon stationary
OBV is non stationaryNon stationary
NATR is non stationaryNon stationary
ATR is non stationaryNon stationary
TSF is non stationaryNon stationary
close is seasonalSeasonal
MA is seasonalSeasonal
EMA is seasonalSeasonal
KAMA is seasonalSeasonal
WMA is seasonalSeasonal
MidPrice is seasonalSeasonal
AD is seasonalSeasonal
OBV is seasonalSeasonal
NATR is seasonalSeasonal
ATR is seasonalSeasonal
Date has unique valuesUnique
EMA has unique valuesUnique
KAMA has unique valuesUnique
WMA has unique valuesUnique
MFI has unique valuesUnique
ROC has unique valuesUnique
NATR has unique valuesUnique
ATR has unique valuesUnique
TSF has unique valuesUnique

Reproduction

Analysis started2026-02-02 00:38:10.792985
Analysis finished2026-02-02 00:38:31.384767
Duration20.59 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
Minimum2010-01-26 00:00:00
Maximum2019-08-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T18:38:32.156001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:32.239228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2044
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.03837
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:32.342493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.049999
Q151.905001
median73.519997
Q393.959999
95-th percentile104.745
Maximum113.93
Range87.720001
Interquartile range (IQR)42.054998

Descriptive statistics

Standard deviation22.143204
Coefficient of variation (CV)0.30317221
Kurtosis-1.3943264
Mean73.03837
Median Absolute Deviation (MAD)21.090004
Skewness-0.024390954
Sum176095.51
Variance490.32149
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6327945398
2026-02-01T18:38:32.428763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:32.622324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:33.416242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
53.900001534
 
0.2%
93.959999084
 
0.2%
100.58999633
 
0.1%
55.259998323
 
0.1%
44.740001683
 
0.1%
102.66000373
 
0.1%
92.190002443
 
0.1%
49.560001373
 
0.1%
103.40000153
 
0.1%
Other values (2034)2376
98.5%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-01T18:38:32.496099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2389
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.079197
Minimum29.173
Maximum112.159
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:33.812641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.173
5-th percentile42.0815
Q151.793001
median73.682
Q394.260999
95-th percentile104.7475
Maximum112.159
Range82.985999
Interquartile range (IQR)42.467999

Descriptive statistics

Standard deviation22.06567
Coefficient of variation (CV)0.30194188
Kurtosis-1.4064354
Mean73.079197
Median Absolute Deviation (MAD)21.184
Skewness-0.032447604
Sum176193.94
Variance486.8938
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4943512815
2026-02-01T18:38:33.881980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:34.073605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:34.818941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
99.09099962
 
0.1%
49.047999952
 
0.1%
58.451000212
 
0.1%
94.529000092
 
0.1%
99.958998872
 
0.1%
64.327000432
 
0.1%
88.816000372
 
0.1%
95.230000312
 
0.1%
81.920998382
 
0.1%
98.479999542
 
0.1%
Other values (2379)2391
99.2%
ValueCountFrequency (%)
29.173000141
< 0.1%
29.232000161
< 0.1%
29.381000141
< 0.1%
29.450000191
< 0.1%
29.45399991
< 0.1%
29.531999971
< 0.1%
29.711999891
< 0.1%
29.871000291
< 0.1%
30.001999861
< 0.1%
30.005999951
< 0.1%
ValueCountFrequency (%)
112.15899961
< 0.1%
112.051
< 0.1%
111.6571
< 0.1%
111.27100071
< 0.1%
110.99400021
< 0.1%
110.68900071
< 0.1%
110.11400071
< 0.1%
109.48300021
< 0.1%
109.46300051
< 0.1%
109.28500061
< 0.1%
2026-02-01T18:38:33.944193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

EMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.081436
Minimum29.287779
Maximum111.98617
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:35.308867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.287779
5-th percentile42.32276
Q151.754779
median73.712009
Q394.339175
95-th percentile104.59845
Maximum111.98617
Range82.698395
Interquartile range (IQR)42.584396

Descriptive statistics

Standard deviation22.032624
Coefficient of variation (CV)0.30148045
Kurtosis-1.4130376
Mean73.081436
Median Absolute Deviation (MAD)21.115887
Skewness-0.033939159
Sum176199.34
Variance485.43654
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5980571509
2026-02-01T18:38:35.405954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:35.655197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:36.499379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
77.385473811
 
< 0.1%
76.709932791
 
< 0.1%
76.151763081
 
< 0.1%
75.558715141
 
< 0.1%
75.353494261
 
< 0.1%
75.694677731
 
< 0.1%
75.92837331
 
< 0.1%
75.421396221
 
< 0.1%
74.65205191
 
< 0.1%
74.149860531
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
29.287778661
< 0.1%
29.321249231
< 0.1%
29.342840381
< 0.1%
29.537273421
< 0.1%
29.739331751
< 0.1%
29.761405611
< 0.1%
30.012638151
< 0.1%
30.05581681
< 0.1%
30.385668451
< 0.1%
30.422970081
< 0.1%
ValueCountFrequency (%)
111.98617381
< 0.1%
111.81596091
< 0.1%
111.64532431
< 0.1%
111.3476041
< 0.1%
111.13761851
< 0.1%
110.75486691
< 0.1%
110.30928131
< 0.1%
109.88689961
< 0.1%
109.35509981
< 0.1%
109.24804021
< 0.1%
2026-02-01T18:38:35.485810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

KAMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.85677
Minimum28.98641
Maximum110.50473
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:36.974595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.98641
5-th percentile41.873558
Q151.524566
median73.332555
Q394.708109
95-th percentile105.11162
Maximum110.50473
Range81.51832
Interquartile range (IQR)43.183543

Descriptive statistics

Standard deviation22.16167
Coefficient of variation (CV)0.30418134
Kurtosis-1.3982586
Mean72.85677
Median Absolute Deviation (MAD)21.467573
Skewness-0.025852569
Sum175657.67
Variance491.13962
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5711298992
2026-02-01T18:38:37.078372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:37.372698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:38.319288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
75.949905411
 
< 0.1%
75.448458091
 
< 0.1%
75.088957031
 
< 0.1%
74.630312671
 
< 0.1%
74.614973391
 
< 0.1%
74.677811881
 
< 0.1%
74.700986781
 
< 0.1%
74.638504111
 
< 0.1%
74.480175851
 
< 0.1%
74.360010621
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
28.986409871
< 0.1%
29.009892931
< 0.1%
29.01083371
< 0.1%
29.026915391
< 0.1%
29.063092761
< 0.1%
29.079548131
< 0.1%
29.099787661
< 0.1%
29.113922431
< 0.1%
29.148627321
< 0.1%
29.181849841
< 0.1%
ValueCountFrequency (%)
110.50473021
< 0.1%
110.48456821
< 0.1%
110.44889861
< 0.1%
110.14778191
< 0.1%
109.50401991
< 0.1%
108.9391511
< 0.1%
108.21942441
< 0.1%
108.11824781
< 0.1%
108.09014681
< 0.1%
108.02457861
< 0.1%
2026-02-01T18:38:37.161526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.065169
Minimum28.844364
Maximum112.62473
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:38.783134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.844364
5-th percentile42.102727
Q151.803364
median73.639453
Q394.218545
95-th percentile104.80009
Maximum112.62473
Range83.780363
Interquartile range (IQR)42.415181

Descriptive statistics

Standard deviation22.080519
Coefficient of variation (CV)0.30220307
Kurtosis-1.4049145
Mean73.065169
Median Absolute Deviation (MAD)21.192181
Skewness-0.030256789
Sum176160.12
Variance487.54931
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5734532147
2026-02-01T18:38:38.871082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:39.114121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:39.723233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
76.443636951
 
< 0.1%
75.746181971
 
< 0.1%
75.172727271
 
< 0.1%
74.57218171
 
< 0.1%
74.369818121
 
< 0.1%
74.741455081
 
< 0.1%
75.100182831
 
< 0.1%
74.772364391
 
< 0.1%
74.143455641
 
< 0.1%
73.702728131
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
28.844363821
< 0.1%
28.966545451
< 0.1%
29.063636541
< 0.1%
29.091999851
< 0.1%
29.288727531
< 0.1%
29.335818311
< 0.1%
29.509999951
< 0.1%
29.747454381
< 0.1%
29.755272741
< 0.1%
29.836908791
< 0.1%
ValueCountFrequency (%)
112.62472691
< 0.1%
112.51436381
< 0.1%
112.21581851
< 0.1%
112.00345431
< 0.1%
111.62654591
< 0.1%
111.12727311
< 0.1%
110.52781831
< 0.1%
109.98672761
< 0.1%
109.7563641
< 0.1%
109.44218251
< 0.1%
2026-02-01T18:38:38.948620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MidPrice
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1492
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.973967
Minimum29.049999
Maximum111.395
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:40.324400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.049999
5-th percentile42.1375
Q151.849999
median73.440002
Q394.242498
95-th percentile104.73
Maximum111.395
Range82.345001
Interquartile range (IQR)42.392499

Descriptive statistics

Standard deviation22.001466
Coefficient of variation (CV)0.30149746
Kurtosis-1.405108
Mean72.973967
Median Absolute Deviation (MAD)21.194996
Skewness-0.030292907
Sum175940.23
Variance484.06449
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5171562925
2026-02-01T18:38:40.416782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:40.666367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:41.307466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
88.974998479
 
0.4%
59.325000769
 
0.4%
73.770000468
 
0.3%
48.185001378
 
0.3%
52.780000697
 
0.3%
69.130001077
 
0.3%
48.910001757
 
0.3%
41.225000387
 
0.3%
94.619998937
 
0.3%
86.635002147
 
0.3%
Other values (1482)2335
96.8%
ValueCountFrequency (%)
29.049999241
 
< 0.1%
29.251
 
< 0.1%
29.465001111
 
< 0.1%
29.515000341
 
< 0.1%
29.695000651
 
< 0.1%
29.789999013
0.1%
29.824998863
0.1%
30.114999771
 
< 0.1%
30.225000381
 
< 0.1%
30.265000342
0.1%
ValueCountFrequency (%)
111.39500051
 
< 0.1%
110.16500092
 
0.1%
109.84000021
 
< 0.1%
109.73500061
 
< 0.1%
109.39500053
0.1%
109.38499836
0.2%
108.79000091
 
< 0.1%
108.45000081
 
< 0.1%
108.22499854
0.2%
108.0799981
 
< 0.1%
2026-02-01T18:38:40.497163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

BOP
Real number (ℝ)

Distinct2384
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.013062093
Minimum-0.96503551
Maximum0.9638981
Zeros6
Zeros (%)0.2%
Negative1171
Negative (%)48.6%
Memory size37.7 KiB
2026-02-01T18:38:41.652301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.96503551
5-th percentile-0.78790313
Q1-0.44421999
median0.021978529
Q30.47215014
95-th percentile0.78487383
Maximum0.9638981
Range1.9289336
Interquartile range (IQR)0.91637013

Descriptive statistics

Standard deviation0.51470277
Coefficient of variation (CV)39.40431
Kurtosis-1.2438306
Mean0.013062093
Median Absolute Deviation (MAD)0.4567609
Skewness-0.040552232
Sum31.492707
Variance0.26491895
MonotonicityNot monotonic
2026-02-01T18:38:41.919655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06
 
0.2%
0.33333333333
 
0.1%
-0.14159265152
 
0.1%
-0.19780256632
 
0.1%
-0.030303730892
 
0.1%
0.29104428752
 
0.1%
-0.10937462752
 
0.1%
0.252
 
0.1%
-0.45333353682
 
0.1%
0.53594794062
 
0.1%
Other values (2374)2386
99.0%
ValueCountFrequency (%)
-0.9650355061
< 0.1%
-0.94478521861
< 0.1%
-0.9339266881
< 0.1%
-0.93137279351
< 0.1%
-0.9302962991
< 0.1%
-0.92452661791
< 0.1%
-0.91018091281
< 0.1%
-0.90860502841
< 0.1%
-0.90785994151
< 0.1%
-0.90711989471
< 0.1%
ValueCountFrequency (%)
0.96389809661
< 0.1%
0.9414768051
< 0.1%
0.93382438191
< 0.1%
0.93119197021
< 0.1%
0.93072187411
< 0.1%
0.93051483471
< 0.1%
0.92899465721
< 0.1%
0.92351367241
< 0.1%
0.92118041461
< 0.1%
0.92105566961
< 0.1%

CMO
Numeric time series

High correlation 

Distinct2408
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.41646609
Minimum-84.250049
Maximum70.748687
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:42.026713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-84.250049
5-th percentile-51.070063
Q1-20.835801
median3.1481428
Q322.700514
95-th percentile44.873305
Maximum70.748687
Range154.99874
Interquartile range (IQR)43.536315

Descriptive statistics

Standard deviation29.509968
Coefficient of variation (CV)70.858033
Kurtosis-0.62584097
Mean0.41646609
Median Absolute Deviation (MAD)21.382522
Skewness-0.25454544
Sum1004.0997
Variance870.83821
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value4.128210546 × 10-19
2026-02-01T18:38:42.126514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:42.378124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:43.162456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-70.164353122
 
0.1%
26.860883652
 
0.1%
32.411962882
 
0.1%
37.102867561
 
< 0.1%
20.998159721
 
< 0.1%
36.995768981
 
< 0.1%
44.776049771
 
< 0.1%
53.127204541
 
< 0.1%
35.582892421
 
< 0.1%
5.6674274311
 
< 0.1%
Other values (2398)2398
99.5%
ValueCountFrequency (%)
-84.250049431
< 0.1%
-75.366925531
< 0.1%
-75.295553161
< 0.1%
-74.078478971
< 0.1%
-73.830146791
< 0.1%
-72.838433091
< 0.1%
-72.170229551
< 0.1%
-71.013290811
< 0.1%
-70.164353122
0.1%
-70.014545271
< 0.1%
ValueCountFrequency (%)
70.748686721
< 0.1%
66.854355341
< 0.1%
66.405252121
< 0.1%
66.336344211
< 0.1%
66.257263871
< 0.1%
64.286749231
< 0.1%
62.892409121
< 0.1%
61.903298011
< 0.1%
61.752699621
< 0.1%
61.38212421
< 0.1%
2026-02-01T18:38:42.208277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MFI
Numeric time series

High correlation  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.445996
Minimum6.4260667
Maximum92.781019
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:43.636067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.4260667
5-th percentile22.400541
Q137.78625
median49.924889
Q361.200823
95-th percentile75.590312
Maximum92.781019
Range86.354952
Interquartile range (IQR)23.414573

Descriptive statistics

Standard deviation16.116577
Coefficient of variation (CV)0.32594301
Kurtosis-0.49641542
Mean49.445996
Median Absolute Deviation (MAD)11.829777
Skewness-0.059477889
Sum119214.3
Variance259.74406
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.434721547 × 10-13
2026-02-01T18:38:43.730157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:43.973241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:44.734859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
23.050243921
 
< 0.1%
13.906030551
 
< 0.1%
7.5637786491
 
< 0.1%
7.5885229311
 
< 0.1%
6.4260666671
 
< 0.1%
15.139663481
 
< 0.1%
24.705433381
 
< 0.1%
23.454574781
 
< 0.1%
21.711122561
 
< 0.1%
27.770552011
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
6.4260666671
< 0.1%
7.1776835211
< 0.1%
7.3244300951
< 0.1%
7.5331065311
< 0.1%
7.5637786491
< 0.1%
7.5885229311
< 0.1%
8.4872161821
< 0.1%
9.6835952711
< 0.1%
9.8430221971
< 0.1%
10.052825191
< 0.1%
ValueCountFrequency (%)
92.781019061
< 0.1%
92.269595641
< 0.1%
91.90632521
< 0.1%
90.951770491
< 0.1%
90.717842761
< 0.1%
90.292494381
< 0.1%
88.876316571
< 0.1%
86.414773831
< 0.1%
86.35579031
< 0.1%
85.985264631
< 0.1%
2026-02-01T18:38:43.808906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ROC
Numeric time series

High correlation  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.056068038
Minimum-26.188495
Maximum25.066768
Zeros1
Zeros (%)< 0.1%
Memory size37.7 KiB
2026-02-01T18:38:45.218187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-26.188495
5-th percentile-10.615505
Q1-3.6674992
median0.39658967
Q33.8022177
95-th percentile9.9244366
Maximum25.066768
Range51.255263
Interquartile range (IQR)7.4697169

Descriptive statistics

Standard deviation6.2975016
Coefficient of variation (CV)112.31892
Kurtosis0.81805824
Mean0.056068038
Median Absolute Deviation (MAD)3.7097377
Skewness-0.066575043
Sum135.18004
Variance39.658526
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.528664944 × 10-11
2026-02-01T18:38:45.315239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:45.568685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:46.396428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-9.46436971
 
< 0.1%
-8.8129752021
 
< 0.1%
-7.5455141511
 
< 0.1%
-8.187429211
 
< 0.1%
-4.5769226861
 
< 0.1%
-2.2652409041
 
< 0.1%
-0.82452894491
 
< 0.1%
-3.8643564281
 
< 0.1%
-4.4942291831
 
< 0.1%
-4.477813781
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
-26.188495031
< 0.1%
-22.578889051
< 0.1%
-21.101751591
< 0.1%
-20.572355971
< 0.1%
-20.373525491
< 0.1%
-19.514126221
< 0.1%
-19.00912651
< 0.1%
-18.971014711
< 0.1%
-18.691263671
< 0.1%
-18.64567951
< 0.1%
ValueCountFrequency (%)
25.066768121
< 0.1%
23.113101611
< 0.1%
22.320192781
< 0.1%
21.58191981
< 0.1%
21.240516751
< 0.1%
21.187580661
< 0.1%
20.91245651
< 0.1%
20.473583881
< 0.1%
20.393907491
< 0.1%
20.13597441
< 0.1%
2026-02-01T18:38:45.396551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WILLR
Numeric time series

High correlation 

Distinct2407
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-47.489292
Minimum-99.175504
Maximum-0.59403532
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:46.868479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-99.175504
5-th percentile-94.781816
Q1-77.929934
median-44.611522
Q3-18.116945
95-th percentile-4.1279348
Maximum-0.59403532
Range98.581469
Interquartile range (IQR)59.812989

Descriptive statistics

Standard deviation31.245387
Coefficient of variation (CV)-0.65794595
Kurtosis-1.4137028
Mean-47.489292
Median Absolute Deviation (MAD)29.379197
Skewness-0.11765718
Sum-114496.68
Variance976.27423
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.631114079 × 10-16
2026-02-01T18:38:46.967238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:47.238646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:48.130727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-12.3983912
 
0.1%
-56.136097962
 
0.1%
-91.41913092
 
0.1%
-52.152335242
 
0.1%
-14.942543861
 
< 0.1%
-4.4736369231
 
< 0.1%
-7.9754486371
 
< 0.1%
-25.995261551
 
< 0.1%
-60.889941881
 
< 0.1%
-69.230718261
 
< 0.1%
Other values (2397)2397
99.4%
ValueCountFrequency (%)
-99.175503981
< 0.1%
-98.931159651
< 0.1%
-98.897642341
< 0.1%
-98.883576841
< 0.1%
-98.823527651
< 0.1%
-98.689967971
< 0.1%
-98.605429141
< 0.1%
-98.548643211
< 0.1%
-98.41090321
< 0.1%
-98.316523981
< 0.1%
ValueCountFrequency (%)
-0.59403532331
< 0.1%
-0.78491751091
< 0.1%
-0.95458505821
< 0.1%
-1.0007645751
< 0.1%
-1.0367634691
< 0.1%
-1.1226342621
< 0.1%
-1.136317661
< 0.1%
-1.1412532131
< 0.1%
-1.2178125211
< 0.1%
-1.2304315471
< 0.1%
2026-02-01T18:38:47.047106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

AD
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2406
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20967486
Minimum-378745.32
Maximum42024321
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:48.595791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-378745.32
5-th percentile3899071.7
Q115613192
median20126457
Q324984211
95-th percentile40236553
Maximum42024321
Range42403067
Interquartile range (IQR)9371019.2

Descriptive statistics

Standard deviation9898323.1
Coefficient of variation (CV)0.47207964
Kurtosis-0.25300755
Mean20967486
Median Absolute Deviation (MAD)4769639.1
Skewness0.26239225
Sum5.0552608 × 1010
Variance9.79768 × 1013
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6939271093
2026-02-01T18:38:48.687407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:48.908870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:49.624501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
15436225.062
 
0.1%
24457105.292
 
0.1%
18014490.072
 
0.1%
36834620.762
 
0.1%
16976306.492
 
0.1%
17523122.431
 
< 0.1%
17205108.51
 
< 0.1%
17386210.741
 
< 0.1%
17296048.41
 
< 0.1%
17205434.431
 
< 0.1%
Other values (2396)2396
99.4%
ValueCountFrequency (%)
-378745.32191
< 0.1%
-246463.75031
< 0.1%
-236423.53881
< 0.1%
-192492.54841
< 0.1%
-39361.13461
< 0.1%
13719.767531
< 0.1%
40006.578681
< 0.1%
61869.910741
< 0.1%
98396.925571
< 0.1%
128646.19621
< 0.1%
ValueCountFrequency (%)
42024321.341
< 0.1%
41914665.051
< 0.1%
41863243.41
< 0.1%
41770772.841
< 0.1%
41722133.341
< 0.1%
41703599.71
< 0.1%
41700615.361
< 0.1%
41681480.671
< 0.1%
41673975.351
< 0.1%
41647456.671
< 0.1%
2026-02-01T18:38:48.765844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

OBV
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2406
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3526028.7
Minimum-18013429
Maximum38169761
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:50.098934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-18013429
5-th percentile-11350176
Q1-3275632.5
median392487
Q33528879
95-th percentile31628782
Maximum38169761
Range56183190
Interquartile range (IQR)6804511.5

Descriptive statistics

Standard deviation12505980
Coefficient of variation (CV)3.5467608
Kurtosis0.64630393
Mean3526028.7
Median Absolute Deviation (MAD)3477919
Skewness1.2285023
Sum8.5012552 × 109
Variance1.5639955 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.9893291022
2026-02-01T18:38:50.200543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:50.458883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:51.219937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
82161542
 
0.1%
234401242
 
0.1%
287079802
 
0.1%
-18506232
 
0.1%
-29968542
 
0.1%
-81899051
 
< 0.1%
-75334891
 
< 0.1%
-80942121
 
< 0.1%
-86903311
 
< 0.1%
-91963671
 
< 0.1%
Other values (2396)2396
99.4%
ValueCountFrequency (%)
-180134291
< 0.1%
-179902281
< 0.1%
-174115891
< 0.1%
-173382721
< 0.1%
-172892941
< 0.1%
-172174641
< 0.1%
-171860921
< 0.1%
-169507821
< 0.1%
-169194321
< 0.1%
-167682781
< 0.1%
ValueCountFrequency (%)
381697611
< 0.1%
380408901
< 0.1%
378939521
< 0.1%
378647761
< 0.1%
374514681
< 0.1%
374268891
< 0.1%
373862751
< 0.1%
372055181
< 0.1%
371607411
< 0.1%
371541421
< 0.1%
2026-02-01T18:38:50.286320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

NATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9437653
Minimum1.1250616
Maximum8.4675329
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:51.695893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.1250616
5-th percentile1.55665
Q12.1656834
median2.6876779
Q33.5153364
95-th percentile5.1826182
Maximum8.4675329
Range7.3424713
Interquartile range (IQR)1.349653

Descriptive statistics

Standard deviation1.133251
Coefficient of variation (CV)0.38496651
Kurtosis2.1431177
Mean2.9437653
Median Absolute Deviation (MAD)0.61243632
Skewness1.2744707
Sum7097.418
Variance1.2842579
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0106491594
2026-02-01T18:38:51.798980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:52.047639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:52.793800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2.6048327131
 
< 0.1%
2.6894948471
 
< 0.1%
2.6497204781
 
< 0.1%
2.7199795671
 
< 0.1%
2.7133557951
 
< 0.1%
2.7065870321
 
< 0.1%
2.6624603191
 
< 0.1%
3.0659700391
 
< 0.1%
3.3704430171
 
< 0.1%
3.2601835231
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
1.1250615851
< 0.1%
1.1401127241
< 0.1%
1.1540216811
< 0.1%
1.1650069081
< 0.1%
1.1679474031
< 0.1%
1.1713779551
< 0.1%
1.1721731481
< 0.1%
1.1743342371
< 0.1%
1.1746524081
< 0.1%
1.1756093681
< 0.1%
ValueCountFrequency (%)
8.4675328731
< 0.1%
8.3062247191
< 0.1%
8.2431645741
< 0.1%
8.0736370511
< 0.1%
7.8371079011
< 0.1%
7.7438253541
< 0.1%
7.7040028071
< 0.1%
7.6104261461
< 0.1%
7.6096259521
< 0.1%
7.5619428811
< 0.1%
2026-02-01T18:38:51.882919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.991511
Minimum0.95446523
Maximum4.1461225
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:53.262089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.95446523
5-th percentile1.1876571
Q11.5717566
median1.9270111
Q32.2878075
95-th percentile3.1441028
Maximum4.1461225
Range3.1916573
Interquartile range (IQR)0.71605092

Descriptive statistics

Standard deviation0.57833757
Coefficient of variation (CV)0.2904014
Kurtosis0.54402956
Mean1.991511
Median Absolute Deviation (MAD)0.35721257
Skewness0.82604191
Sum4801.5329
Variance0.33447435
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.01288243966
2026-02-01T18:38:53.363433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:53.616505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:54.413408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.9460704961
 
< 0.1%
1.9813508041
 
< 0.1%
1.9512541441
 
< 0.1%
1.982593091
 
< 0.1%
2.0195507261
 
< 0.1%
2.0902972561
 
< 0.1%
2.0495620431
 
< 0.1%
2.2424504681
 
< 0.1%
2.3994184661
 
< 0.1%
2.3437459151
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
0.95446522891
< 0.1%
0.95716391321
< 0.1%
0.97942401051
< 0.1%
0.98156089081
< 0.1%
0.98168733731
< 0.1%
0.98976842281
< 0.1%
1.0039887571
< 0.1%
1.0095095221
< 0.1%
1.0112891411
< 0.1%
1.0147847021
< 0.1%
ValueCountFrequency (%)
4.146122481
< 0.1%
4.1078280611
< 0.1%
4.061978221
< 0.1%
4.011554781
< 0.1%
3.9354218811
< 0.1%
3.9243009331
< 0.1%
3.8470220071
< 0.1%
3.8421772641
< 0.1%
3.8404953461
< 0.1%
3.8371548961
< 0.1%
2026-02-01T18:38:53.447618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

TRANGE
Real number (ℝ)

High correlation 

Distinct766
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9915678
Minimum0.47999954
Maximum11.129997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:54.851461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.47999954
5-th percentile0.88000107
Q11.3300018
median1.7799988
Q32.420002
95-th percentile3.7050018
Maximum11.129997
Range10.649998
Interquartile range (IQR)1.0900002

Descriptive statistics

Standard deviation0.97691251
Coefficient of variation (CV)0.49052435
Kurtosis8.0863809
Mean1.9915678
Median Absolute Deviation (MAD)0.51999664
Skewness2.0067812
Sum4801.67
Variance0.95435804
MonotonicityNot monotonic
2026-02-01T18:38:54.931425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.518
 
0.7%
1.6100006117
 
0.7%
1.7517
 
0.7%
114
 
0.6%
1.93000030514
 
0.6%
1.6399993914
 
0.6%
1.52999877914
 
0.6%
1.84999847413
 
0.5%
1.66999816913
 
0.5%
1.31999969513
 
0.5%
Other values (756)2264
93.9%
ValueCountFrequency (%)
0.47999954221
< 0.1%
0.48999786381
< 0.1%
0.51
< 0.1%
0.52000045782
0.1%
0.55000305181
< 0.1%
0.56999969481
< 0.1%
0.59000015262
0.1%
0.60000228881
< 0.1%
0.61999893191
< 0.1%
0.62999725341
< 0.1%
ValueCountFrequency (%)
11.129997251
< 0.1%
8.2900009161
< 0.1%
81
< 0.1%
7.7900009161
< 0.1%
7.751
< 0.1%
7.6499938961
< 0.1%
7.3400039671
< 0.1%
7.0999984741
< 0.1%
7.0500030521
< 0.1%
6.7099990841
< 0.1%

TSF
Numeric time series

High correlation  Non stationary  Unique 

Distinct2411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.024832
Minimum26.556923
Maximum115.04439
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:38:55.031866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.556923
5-th percentile41.597857
Q152.025494
median73.176813
Q393.957196
95-th percentile105.22709
Maximum115.04439
Range88.487472
Interquartile range (IQR)41.931702

Descriptive statistics

Standard deviation22.246204
Coefficient of variation (CV)0.30463889
Kurtosis-1.3737664
Mean73.024832
Median Absolute Deviation (MAD)21.007473
Skewness-0.018804623
Sum176062.87
Variance494.89357
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5978801501
2026-02-01T18:38:55.118713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:38:55.355769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-01T18:38:56.017626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
73.579011521
 
< 0.1%
72.785494371
 
< 0.1%
72.205494721
 
< 0.1%
71.724395671
 
< 0.1%
71.967911691
 
< 0.1%
72.973956681
 
< 0.1%
73.825496211
 
< 0.1%
73.622199011
 
< 0.1%
72.823408271
 
< 0.1%
72.628462151
 
< 0.1%
Other values (2401)2401
99.6%
ValueCountFrequency (%)
26.556922891
< 0.1%
26.675714161
< 0.1%
27.112527871
< 0.1%
27.386043931
< 0.1%
27.508570951
< 0.1%
27.530769471
< 0.1%
27.770109641
< 0.1%
27.795824431
< 0.1%
28.042306981
< 0.1%
28.196264331
< 0.1%
ValueCountFrequency (%)
115.04439461
< 0.1%
114.43120851
< 0.1%
114.18791261
< 0.1%
113.29384511
< 0.1%
112.67208841
< 0.1%
111.81538471
< 0.1%
111.36846191
< 0.1%
111.11615331
< 0.1%
111.03461661
< 0.1%
110.76626391
< 0.1%
2026-02-01T18:38:55.197740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-01T18:38:30.195596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.302666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.225191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.126553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.185209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.303641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.570522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.541611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.635113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.778853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.760519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.758067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.901647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.857426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.947382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.991499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.033757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.259845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.353133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.275423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.175531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.248543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.354530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.624849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.601606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.695140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.832526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.816889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.921721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.959558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.914435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.006784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.050591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.086767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.309953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.405231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.326926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.225079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.310469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.416862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.703706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.662605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.751795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.882443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.868711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.978147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.013164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.968069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.063723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.108366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.142317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.388971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.454499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.376535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.273736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.372186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.517327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.760891image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.723757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.807019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.933966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.923632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.036686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.067687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.020943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.122966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.167913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.195864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.448600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.514083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.435504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.332079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.440345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.606634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.820550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.794637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.869971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.996290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.984208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.102442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.133156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.080796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.189655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.234683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.260025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.501991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.563986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.485402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.515855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.502761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.661468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.872992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.854410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.921720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.046615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.037374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.161745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.187351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.134373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.250134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.292463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.314804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.554059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.614627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.534833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.567193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.563513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.714657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.924094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.917342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.081428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.098799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.093147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.220003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.244090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.189873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.308531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.349208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.390203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.616466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.677166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.595838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.630868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.634866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.776295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.986994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.986562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.148398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.158925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.155185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.289791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.308288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.251061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.377138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.414777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.610627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.674866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.734174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.652765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.689400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.702352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.850690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.044529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.055815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.210630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.226958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.217068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.354593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.369619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.311094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.442209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.479016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.675096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.734620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.787179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.702971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.741903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.763246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.923120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.095922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.116658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.267705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.289795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.290557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.415677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.420930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.365091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.501438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.534830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.730544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.814807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.839206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.753432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.793055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.825548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.978367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.151202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.180848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.326393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.342788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.352406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.474104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.474587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.422076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.560261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.595348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.786223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.867854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.892879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.806050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.852614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.891798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.032881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.205332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.246015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.386889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.402068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.412281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.535762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.530663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.479320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.623358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.655061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.845656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.921891image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:13.947263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.858911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.907088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.953730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.093987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.260090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.310776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.448436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.461625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.467505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.593930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.583779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.536735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.683846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.713232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.900829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.976129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.002964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.913437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.962763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.030138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.151662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.318064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.376605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.511093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.537663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.528529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.654825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.641649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.593661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.744047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.774755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:29.963159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:31.032830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.061710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.968353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.021413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.112160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.208190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.378575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.444193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.576541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.595730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.587410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.720055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.697242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.655642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.807903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.837489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.023240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:31.090918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.117769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.022965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.076855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.180072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.409356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.436415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.508898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.660740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.654340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.649054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.781673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.753988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.826902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.871023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.896291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.084291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:31.143583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:14.174849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:15.075401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:16.132454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:17.243350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:18.491577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:19.490449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:20.574892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:21.721577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:22.709313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:23.704731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:24.844293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:25.806832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:26.888772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:27.933044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:28.979259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:30.140140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T18:38:56.697566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ADATRBOPCMOEMAKAMAMAMFIMidPriceNATROBVROCTRANGETSFWILLRWMAclose
AD1.000-0.4740.012-0.010-0.121-0.118-0.123-0.005-0.121-0.2500.642-0.035-0.298-0.130-0.039-0.123-0.126
ATR-0.4741.000-0.025-0.1500.2830.2810.281-0.0940.2810.498-0.269-0.0600.6540.272-0.0760.2800.277
BOP0.012-0.0251.0000.3880.0080.0040.0030.1610.004-0.0680.0740.292-0.0760.0170.4700.0090.059
CMO-0.010-0.1500.3881.0000.0560.0380.0460.7710.042-0.2400.1610.865-0.2090.1330.9290.0740.140
EMA-0.1210.2830.0080.0561.0000.9981.0000.0340.999-0.6400.3620.0060.1820.9940.0381.0000.995
KAMA-0.1180.2810.0040.0380.9981.0000.9980.0230.998-0.6400.363-0.0110.1840.9910.0190.9980.992
MA-0.1230.2810.0030.0461.0000.9981.0000.0290.999-0.6390.361-0.0060.1830.9930.0250.9990.992
MFI-0.005-0.0940.1610.7710.0340.0230.0291.0000.023-0.1680.1420.720-0.1300.1100.7260.0520.093
MidPrice-0.1210.2810.0040.0420.9990.9980.9990.0231.000-0.6400.360-0.0140.1820.9920.0190.9980.992
NATR-0.2500.498-0.068-0.240-0.640-0.640-0.639-0.168-0.6401.000-0.547-0.1290.349-0.649-0.168-0.643-0.648
OBV0.642-0.2690.0740.1610.3620.3630.3610.1420.360-0.5471.0000.090-0.1760.3640.1350.3630.367
ROC-0.035-0.0600.2920.8650.006-0.011-0.0060.720-0.014-0.1290.0901.000-0.1260.0880.8720.0240.085
TRANGE-0.2980.654-0.076-0.2090.1820.1840.183-0.1300.1820.349-0.176-0.1261.0000.171-0.1620.1790.168
TSF-0.1300.2720.0170.1330.9940.9910.9930.1100.992-0.6490.3640.0880.1711.0000.1090.9970.996
WILLR-0.039-0.0760.4700.9290.0380.0190.0250.7260.019-0.1680.1350.872-0.1620.1091.0000.0530.124
WMA-0.1230.2800.0090.0741.0000.9980.9990.0520.998-0.6430.3630.0240.1790.9970.0531.0000.996
close-0.1260.2770.0590.1400.9950.9920.9920.0930.992-0.6480.3670.0850.1680.9960.1240.9961.000

Missing values

2026-02-01T18:38:31.249007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T18:38:31.337120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DatecloseMAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2010-01-262010-01-2674.70999977.50600177.38547475.94990576.44363778.079998-0.363057-50.44267423.050244-9.464370-91.21421998396.925575-1320283.02.6048331.9460701.57000073.579012
2010-01-272010-01-2773.66999876.79400076.70993375.44845875.74618276.660000-0.418035-55.95138213.906031-8.812975-90.97347740006.578683-1676462.02.6894951.9813512.43999572.785494
2010-01-282010-01-2873.63999976.19300076.15176375.08895775.17272776.505001-0.070513-56.1077537.563779-7.545514-91.23895313719.767531-1969373.02.6497201.9512541.55999872.205495
2010-01-292010-01-2972.88999975.54300075.55871574.63031374.57218275.869999-0.418410-60.0476287.588523-8.187429-96.006951-192492.548422-2304643.02.7199801.9825932.38999971.724396
2010-02-012010-02-0174.43000075.18600075.35349474.61497374.36981875.7900010.636002-32.8425986.426067-4.576923-79.818357-39361.134604-2027232.02.7133562.0195512.50000071.967912
2010-02-022010-02-0277.23000375.00700175.69467874.67781274.74145575.7300000.7607971.11432715.139663-2.265241-41.747521283101.563080-1660963.02.7065872.0902973.01000272.973957
2010-02-032010-02-0376.98000374.94300175.92837374.70098775.10018375.395000-0.006575-1.38640324.705433-0.824529-42.622915128646.196177-2052257.02.6624602.0495621.52000473.825496
2010-02-042010-02-0473.13999974.64900175.42139674.63850474.77236475.230000-0.831578-30.65578223.454575-3.864356-89.550054-236423.538763-2576149.03.0659702.2424504.75000073.622199
2010-02-052010-02-0571.19000274.31400174.65205274.48017674.14345673.770000-0.416666-40.60298721.711123-4.494229-82.487024-378745.321896-3172291.03.3704432.3994184.44000272.823408
2010-02-082010-02-0871.88999973.97700074.14986174.36001173.70272873.770000-0.179013-32.99373927.770552-4.477814-74.921304-246463.750290-2826653.03.2601842.3437461.62000372.628462
DatecloseMAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2019-08-132019-08-1357.09999854.66700054.99506656.17639854.47381854.6700000.72699313.24570754.528457-1.636522-20.7229083.963241e+0738169761.03.6619712.0909853.26000253.636813
2019-08-142019-08-1455.23000054.33200055.03778156.14844154.57618254.255001-0.524307-1.68087953.700590-5.718679-43.2530183.954263e+0737451468.03.9203342.1652003.12999753.756263
2019-08-152019-08-1554.47000154.38400054.93454956.13617154.60127353.995001-0.275641-7.20414653.5035610.963856-52.4096253.948849e+0736923602.03.8956702.1219721.56000153.716264
2019-08-162019-08-1654.86999954.30500054.92281256.12364354.68963653.9950010.092197-3.79430651.674289-1.419333-47.5903753.946580e+0737091947.03.7745882.0711171.41000053.965384
2019-08-192019-08-1956.20999954.45700055.15684656.12510255.03600053.9950010.7961787.19337849.2356432.779302-31.4457933.955044e+0737205518.03.6209262.0353231.57000054.870768
2019-08-202019-08-2056.34000054.72800055.37196556.13282455.37836353.9950010.1818198.24046749.3474265.053140-22.0883703.994999e+0737864776.03.5218821.9842281.32000055.967142
2019-08-212019-08-2155.68000055.18700055.42797256.08875855.55145454.705000-0.2341761.76379158.2981108.984146-25.7554063.936181e+0737160741.03.5117721.9553551.58000256.134725
2019-08-222019-08-2255.34999855.46800055.41379556.04869355.58109054.920000-0.366460-1.51024550.6616785.348301-30.5036333.912631e+0736539168.03.4881421.9306871.61000156.451648
2019-08-232019-08-2354.16999855.43499955.18765056.03481455.34509055.355001-0.500001-12.67278750.799555-0.605508-47.4820533.895530e+0735732017.03.6207341.9613522.35999756.271098
2019-08-262019-08-2653.63999955.30599954.90625955.98277155.01872755.2150000.169565-17.34773850.832291-2.348445-55.1079343.867779e+0735052995.03.7016051.9855412.29999955.769889